Statistical Computing Using R/S

Instructor(s): John Fox, Sociology

The statistical programming language and computing environment S has become the de facto standard among statisticians. The S language has two major implementations: the commercial product S-PLUS, and the free, open-source R, which is the subject of these introductory lectures. A statistical package, such as SPSS, is primarily oriented toward combining instructions with rectangular case-by-variable datasets to produce (often voluminous) printouts. Such packages make routine data analysis relatively easy, but they make it relatively difficult to do things that are innovative or nonstandard, or to add to the built-in capabilities of the package. In contrast, a good statistical computing environment makes routine data analysis easy and also supports convenient programming. R fulfills all these requirements and users can readily extend its already impressive facilities. R is also particularly capable in the area of statistical graphics. The first lecture provides basic orienting information, while the second introduces statistical models in R, including linear and generalized linear models. This is followed by a four-session hands-on computer workshop, which picks up where the introductory lectures leave off. The object is to provide some facility in the use of R, including manipulating data, writing programs, constructing nonstandard and publication-quality statistical graphs, and using R packages.